We extract style codes, sizing grids, geo-specific pricing, and discount velocity from PrettyLittleThing. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from prettylittlething.com. All fields typed and schema-versioned.
"style_code": "CMA1234", "title": "Black Slinky Ruched Front Shirt", "category": "Clothing > Tops > Shirts", "price": 15.0, "list_price": 25.0, "discount_pct": 40, "colour": "Black", "fabric_composition": "95% Polyester 5% Elastane"
| # | style_code | title | category | sub_category | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from prettylittlething.com. All fields typed and schema-versioned.
"style_code": "CMA1234", "region": "UK", "current_price": 15.0, "original_price": 25.0, "is_on_sale": true, "promo_text": "USE CODE: EXTRA10", "sizes_in_stock": "['4', '6', '8', '10']", "sizes_out_of_stock": "['12', '14', '16']"
| # | style_code | region | currency | current_price | original_price | is_on_sale |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Categories & Taxonomy objects from prettylittlething.com. All fields typed and schema-versioned.
"category_id": "cat_tops", "category_name": "Tops", "breadcrumb": "Home > Clothing > Tops", "parent_category": "Clothing", "product_count": 4821, "url": "https://www.prettylittlething.com/clothing/tops.html", "sort_order": "Recommended"
| # | category_id | category_name | breadcrumb | parent_category | product_count | url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our PLT scraper handles fast-moving inventory, geo-fenced pricing, and heavy frontend rendering — delivering clean SKU-level data without the bot-blocking headaches.
Map every product to its unique style code. Capture title, category breadcrumbs, colour variants, and high-resolution image URLs.
Extract size availability grids. Differentiate between in-stock, out-of-stock, and low-stock sizes for precise demand forecasting.
Track localised pricing across PLT's UK, US, EU, and AU storefronts. Monitor region-specific base prices and active promotions.
Log list price vs current price, discount percentages, and promotional banner text (e.g., 'Pink Friday' or sitewide discount codes).
Extract material breakdowns, care instructions, and model sizing details directly from the product description DOM.
Fast fashion inventory moves quickly. Configure hourly or daily runs to catch flash sales, markdown velocity, and restocks.
Brief in. Clean data out.
Provide category URLs, specific style codes, or target regions. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for prettylittlething.com.
Schema validation, null-rate checks, price-outlier detection, and size-grid verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fast fashion sites deploy aggressive caching and bot protection to shield pricing logic. Here's how we ensure reliable extraction.
PLT uses advanced bot mitigation to block datacenter IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass perimeter security.
Pricing and stock availability differ vastly between PLT's US, UK, and AU sites. We route requests through region-matched residential nodes to capture accurate local pricing and promo codes without triggering redirection loops.
Size availability and dynamic pricing modules rely heavily on client-side rendering. We run full Playwright browser sessions to execute JavaScript, ensuring accurate stock-status capture across all size variants.
Fast fashion requires high-frequency tracking. We maintain a hash index of last-seen values per style code. Subsequent runs only push diffs — isolating price drops and stockouts without redundant data transfer.
PLT frequently updates its frontend architecture for major sale events. Our extraction logic relies on multiple fallback chains — targeting underlying JSON data layers and API endpoints before falling back to DOM parsing.
Fashion retailers track PLT's base pricing and discount velocity to calibrate their own promotional calendars and markdown strategies.
Merchandising teams monitor new arrivals and category density to identify emerging micro-trends and fabric preferences.
Pricing algorithms consume historical discount data to model optimal markdown curves based on PLT's clearance behaviour.
Analysts track size-level stockouts across categories to estimate sales velocity and inform fast-fashion procurement cycles.
Computer vision teams extract high-resolution product imagery paired with detailed fabric and style metadata to train generative fashion models.
Arbitrageurs monitor flash sales and extreme markdowns in specific regions to identify cross-border margin opportunities.
"PrettyLittleThing cycles inventory faster than almost any other retailer. If you aren't tracking size-level stock daily, your pricing models are operating blind."
Extracting fast fashion data requires handling constant DOM changes, aggressive CDN caching, and geo-fenced pricing. DataFlirt manages the residential proxy pools, JavaScript execution, and schema normalisation so your data scientists can focus on markdown optimisation — not scraping infrastructure.
Everything supported by our prettylittlething.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across UK/US/EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About prettylittlething.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail sites is generally permissible under applicable law in the UK and US. DataFlirt targets only public, non-authenticated product, pricing, and category data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies targeted to specific regions, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403/CAPTCHA rate spikes and trigger pool rotation automatically.
Yes. We configure pipelines to route through region-specific proxy nodes (e.g., UK, US, AU) to capture the exact localised pricing, currency, and promotional banners displayed to users in those territories.
For fast fashion, we typically configure daily or sub-daily runs. Real-time streaming pipelines can achieve sub-60-minute latency for price and availability signals on a defined list of priority style codes.
Yes. The pipeline captures the full size grid per product, explicitly mapping which sizes are in-stock versus out-of-stock at the time of extraction.
Our smallest packages start at a defined category or style code list with daily delivery. For full-catalogue extraction across multiple regions, we price based on compute volume and proxy bandwidth. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off category export or continuous tracking of discount velocity and size availability — we scope, build, and operate the pipeline. Tell us what you need.
